"We don't celebrate birthdays"

"I had one birthday a few decades ago.. when I was born. and that was that"

"Why is everyone always living in the past? I'm post-birthday celebrations"

"I have no desire to draw attention to myself"

"I don't celebrate birthdays... which allows me to still look the same as I did 10 years ago"

You've just read a Β small smattering of the excuses I've employed throughout the past [redacted] years in my efforts to avoid all displays of joy, celebration, and the general merriment that typically accompany the anniversary of a life's origin. This year however, I decided to try something different. I decided to have people over. I love my friends and I've been hella busy, so I hadn't seen a lot of them. Thus, the Kickback King was born.

So I got to work..

  • I hired a party planning consultant
    • called my mixiest friends
  • secured corporate sponsors
    • put &computers on a flier
  • contracted out a digital design firm
    • blocked out 45 minutes on my own calendar
  • marketed the event
    • text more friends my address

The night was a success, I caught up with old friends, met new people, connected total strangers, and had an excellent time. It was a true rager. And so, I write this piece in commemoration of one of my best birthday celebrations ever (low bar).

the creative multi-media digital consulting agency's work

Attendance: Expectation != Reality

As the flyer notes, the party started at 8pm. Leaning on my planning consultant's infinite wisdom, we gave a time an hour earlier than what we really wanted because.. given my friends' cultural proclivities we just knew they'd be about an hour late.

Since my apartment sucks and no one can get directly to my door, I had a text or a call indicating the arrival time of everyone at the party. I used these digital records to construct the distribution of party-goers over time. What the records showed is that while you might be expecting one thing, what actually happens could be entirely different. Here is a graphical representation of the difference between what we expected and what actually happened on the night of the party.

We thought we'd see the turquoise distribution of attendees, but we experienced the purple distribution.

A couple of things to note.

  • We expected people to be late, but not that late.
  • People were still arriving after the advertised end of the party (12 am)
  • More people at 2 am than at 8 pm indicates overnight guests... for good reason. (see next section)


At about 11:30 pm, near the peak of party attendance, we broke out the Taboo. We're drinking, we're laughing, we're talking shit... 3 of my favorite activites.

A couple of rounds pass and someone asks what the score is.. a response rings out: "27 to 13" they said.. "our lead". About 47 seconds later, as I slowly came to the realization that I was on the 13 point team, I knew something was horribly wrong. As a world-renowned-word-smithing-taboo-mvp, there is only one reason my team could ever not be winning. I. am. drunk.

Earlier that week, my aforementioned party consultant had the great idea to create our own Sangria. A fruity blend of sweet juice, liquor, and wine; the perfect complement to a sweltering summer afternoon.. served in my stuffy lil apartment in the middle of winter. πŸ™ƒ

So. After a few (read: 5ish) cups of this sugary goodness, it occurred to me that I had no idea how strong it was relative to typical off-the-shelf drinks. Naturally, I also began to wonder if we had saved any money by making our own mixture.. Luckily, some dumpster diving enabled us to answer each of these questions. Behold, a recipe:

Twelve-Seven Famous Sangria Recipe

The above recipe yields 6+ liters of 8.4% alcohol by volume (abv) for about $42. Which for reference, is about 2x what you would pay for the same volume of beer, which we'll say is normally ~7% abv. At its core this recipe is juiced-down wine; easier to drink yet with slightly more alcohol than the typical brewski. Given that everyone likes juice, in my opinion, its a safer bet to make your own mix than just getting a bunch of beer for your next kickback. &computers party consulting at your service.

The Tunes

Lastly, some insights we gained from an analysis of the night's playlist. It's been linked below and is available for streaming on Spotify.

Energy, Valence, and Danceability

Did you know that Spotify makes a bunch of audio feature data available for each song?

There are a lot of features, but the 4 that I found to be the most interpretable were:

  • Tempo
  • Energy
  • Valence
  • Danceability

Per the Spotify documentation:

The overall estimated tempo of a track in beats per minute (BPM). In musical terminology, tempo is the speed or pace of a given piece and derives directly from the average beat duration.

Energy is a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity. Typically, energetic tracks feel fast, loud, and noisy. For example, death metal has high energy, while a Bach prelude scores low on the scale. Perceptual features contributing to this attribute include dynamic range, perceived loudness, timbre, onset rate, and general entropy.

Valence is a measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry).

Danceability describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. A value of 0.0 is least danceable and 1.0 is most danceable.

When I saw that all of this data was available I had an idea... Since I had made the playlist & everyone loved it && I am internationally renowned for my music curation skills (2 lies and a truth). I figured I could look at a few audio features of the songs and get a data-driven affirmation of how well the songs were mixed, visualize the transitions I put in, and see how I masterfully orchestrated the party vibes in a controlled & orderly fashion.

Playlist Valence, Energy, and Danceability 

A few takeaways:

  • The party had a pretty good balance of high and low intensity tracks
  • A visual inspection shows that Valence1 & Energy, despite having similar sounding definitions, seem to not actually be that closely related?
  • Danceability1 was high throughout, so we were definitely lit
  • Although someone thought they were DJing & "masterfully orchestrating vibes".. that data shows that this wasn't it. πŸ€¦πŸΏβ€β™‚οΈ
    • The consistent jumps from peaks to valleys seem to indicate that the playlist may have had poor flow
Playlist Tempo in Beats Per Minute (BPM)

We're showing tempo in a separate visual because it isn't scaled 0-1 like the other audio features.

This graph tells a much different story than the previous one. You can see a couple pockets of similar tempo songs for instance between 11:15 pm and 11:40 pm and again from 12:18 am to about 12:40 am. These smooth sections with low variance indicate that someone may have been trying to do a little something something with the song order.. a slow jams hour mayhaps? Maybe the DJing wasn't thattt bad 😌.

Last but not least, here's where the artists on the playlist hail from. The darker & larger the spot on the map, the more songs from distinct artists in those regions.

Heat Map of Artists on Playlist

Key observations:

  • Juice county & surrounding area are well represented.. slight DJ bias 😎
  • Some international riddims in here
  • The Atlanta music scene is truly prolific


As you've probably heard by now this was one of the best kickbacks of the decade as voted by the international body that decides on such matters. Big thanks for reading & an even bigger thanks for those who came.

  • this is the first event &computers has ever "sponsored"
  • when hosting anything shift your time expectation forward like 2 hours
  • beer may be cheapest, but everyone likes sangria
  • we shoulda given out party favors, maybe mouse pads? what y'all think?
  • real DJs should use some of the audio features that spotify collects to automate and/or advise on the vibe curation + mixing & transitions..

As always, let us know what you think, what type of data and/or visualizations that might be interseting.

1 What is the most high-energy, dance-inducing, happy-sounding song on the playlist? Beyonce's "Before I Let Go"? Well, it has a Valence ("happiness sounding metric") of 0.435, a Danceability of 0.713, and an Energy of 0.842. While the data is interesting to look at and allegedly rooted in some audio processing technology it may or may not be the best reflection of reality. However, its worth noting that the real-life danceability of the track (and it's Frankie Beverly & Maze predecessor) may be more rooted in culture & tradition than in its sonic features. I'm still struggling to find a similar defense of the low valence rating for the track, given that its one of the happiest sounding songs I've ever heard.

Further Reading & References